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, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular geometries. Current simulation-based approaches require complex 3D meshes and are often too slow
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Your Job: We are looking for a PhD student to contribute to the development of fast, accurate, and physics-informed machine learning models for predicting blood flow in patient-specific vascular
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of receiving the link) into the media database. Please upload video files (mp4, maximum resolution 1080 pixels) only. The composition subject subject as well as sound engineering, sound studies, etc
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are researching this and similar questions. Our goal is to systematically optimise the interaction between people, organisations and technology. With us, your theory also passes the practical test. Bring your
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requirements, see below): Jordan University of Science and Technology, Irbid (JUST) M.Sc. Computer Engineering* M.Sc. Network Engineering and Security* M.Sc. Radiologic Technology** M.Sc. Medical Laboratory
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personal data is saved by the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the application. Submitting
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the fields of medicine, biology, chemistry, physics, technology, and the humanities. Since 1948, MPI researchers have been awarded 21 Nobel prizes, which testifies to the quality and innovation of MPI research
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the DAAD in accordance with the Federal Data Protection Act and with the EU Data Protection Regulation insofar as this data is needed to process the application. Submitting an application General information
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. Infectious Diseases Prevention and Control M.Sc. Medical Imaging Technology M.Sc. Pharmaceutical Sciences Master‘s Degree in Law M.Sc. Electronics and Computer Engineering Al-Quds Open University M.Sc